QUANTIFYING URBAN VEGETATION COVERAGE CHANGE WITH A LINEAR SPECTRAL MIXING MODEL: A CASE STUDY IN XI'AN, CHINA

With the rapid development of urban area of Xi'an in recent years, the contradiction between ecological environmental protection and urban development has become prominent. The traditional remote sensing classification method has been unable to meet the accuracy requirements of urban vegetation monitoring. Therefore, how to quickly and accurately conduct dynamic monitoring of urban vegetation based on the spectral component characteristics of vegetation is urgent. This study used the data of Landsat 5 TM and Landsat 8 OLI in 2011, 2014 and 2017 as main information source and LSMM, region of variation grid analysis and other methods to analyse the law of spatial-temporal change of vegetation components in Xi'an urban area and its influencing factors. The result shows that: (1) The average vegetation coverage of the study area from 2011 to 2017 reached more than 50 %, meeting the standard of National Garden City (great than 40 %). The overall vegetation coverage grade was high, but it had a decreasing trend during this period. (2) The vegetation in urban area of Xi'an experienced a significant change. From 2011 to 2017, only 30 % of the low-covered vegetation, 24.39 % of the medium-covered vegetation and 20.15 % of the high-covered vegetation remained unchanged, while the vegetation in the northwest, northeast, southwest and southeast of the edge of the city's third ring changed significantly. (3) The vegetation quality in urban area of Xi'an has decreased from 2011 to 2014 with 6.9 % of vegetation coverage reduced; while from 2014 to 2017, the overall vegetation quality of this area has improved with 2.1 % of the vegetation coverage increased, which was mainly attributed to urban construction and Urban Green Projects. This study not only can obtain the dynamic change information of urban vegetation quickly, but also can provide suggestions and data support for urban planning of ecological environmental protection.